Article

Comparison of Methodologies Used in Homicide Investigations to Collect, Prioritize, and Eliminate Persons of Interest: A Case Study of Three Dutch Real-World Homicide Cases

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  • TNO / Police Academy
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Abstract

This paper provides a comparison between four methodologies that assist criminal investigators in homicide investigations. The Person of Interest Priority Assessment Tool, Trace Investigate and Evaluate, Rasterfahndung, and Analysis of Competing Hypotheses are compared on their performance in the collection, prioritization, and elimination phase of homicide cases in today's digital era. Three recent Dutch homicide cases are used. The use of categories during collection can assist criminal investigators in the early inclusion of the perpetrator into the investigation , however, in this digital era, the number of persons of interest becomes too large to humanly handle. All four methodologies use techniques to assign weight to pieces of evidence; further research is required to evaluate the effectiveness of these techniques when the amount of pieces of evidence explodes. The use of pre-set elimination categories shows the least promising result leaving most persons of interest not-eliminated by the currently used methodologies.

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... Sutmuller, den Hengst, Barros, and van Gelder [18] provided a comparison between these four methodologies that are currently being used in homicide investigations. The four methodologies were evaluated across three recently solved Dutch homicide cases using the following questions: can the methodology incorporate the name of the perpetrator into the investigation within the first two weeks (collection) and can the methodology prioritize the perpetrator within the top ten percent of persons of interest (prioritize)? ...
... The methodologies showed comparable and modest results. All methodologies failed to meet the performance criterion for collection and prioritization in one of the three cases [18]. In addition, Sutmuller et al. [18] showed that a large number of persons of interest, tens of thousands, would be incorporated using the methodologies and stated that it is important to take into account the reliability and credibility of the source of evidence [18]. ...
... All methodologies failed to meet the performance criterion for collection and prioritization in one of the three cases [18]. In addition, Sutmuller et al. [18] showed that a large number of persons of interest, tens of thousands, would be incorporated using the methodologies and stated that it is important to take into account the reliability and credibility of the source of evidence [18]. ...
Article
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Homicide investigators in the digital era have access to an increasing amount of data and the processing of all persons of interest and pieces of evidence has become nearly impossible. This paper describes the development and evaluation of a case-specific element library (C-SEL) that can be used to incorporate and prioritize persons of interest in homicide investigations. In a survey, 107 experts in the field of criminal investigation assigned an initial score to the elements. Each element was extended with underlying factors that can be used to adjust the initial score based on the relevance and credibility of the source. A case study was conducted using three Dutch real-world cases to evaluate the methodology. The results look promising and are better than four methodologies currently used in practice.
... It does not provide a reasoning concerning how to collect POIs and merely presumes the POIs have already been identified in a certain case. This is possibly because the method was developed in response to a certain homicide case that had thousands of POIs already in scope (Sutmuller, den Hengst, Barros, & van Gelder, 2018). It is a way of ranking priorities and tries to be as objective as possible in the process of creating and assessing the questionnaire but it can still also be subjective in some parts. ...
... Basic rules are given that describe the appropriate weighting, yet the final decision is left to the creator. The use of benchmark elements in POIPAT makes several items of evidence share the same weight, making the method less discriminating with respect to POIs (Sutmuller et al., 2018). It is otherwise an efficient method ensuring the proper use of resources, helping investigators to save money and time and to initially focus on the most likely suspects and continue from there. ...
... The library of elements is nicely described and includes many examples of pre-set categories of elements, which are usually important in an investigation, albeit nowadays it could use an improvement. The elimination categories in the basic rules do not explicitly include new classes of evidence such as telecom data and camera footage so the integration of new classes of forensic evidence as pre-set elimination categories could help better discriminate POIs (Sutmuller et al., 2018). Like any similar tool, when used properly the POIPAT assists the investigator or police force of jurisdiction with a decision-making formula (Sekela, 2010). ...
Article
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Purpose: The purpose of this paper is to present an elimination method called the POIPAT and demonstrate its usefulness in eliminating suspects in cold-case investigations. Design/Methods/Approach: The paper presents a SWOT analysis of the POIPAT method that considers the strengths, weaknesses, opportunities and threats connected to cold-case investigations. Findings: The POIPAT is mostly used in cold homicide cases to, with the help of a compiled questionnaire, assist investigators eliminate suspects by evaluating and arranging them on levels of importance. The more points a suspect gathers, the more likely they are the perpetrator. The method's advantages include the effective use of resources, the focus on the most likely perpetrators, and the questionnaire's objectivity. The biggest deficiencies are possible subjectivity in determining the importance of the elements and lack of knowledge of the method, together with the use of a questionnaire that is not adapted to the Slovenian situation. While the method is promising and useful, it only holds heuristic value. Research Limitations/Implications: The limitations mainly lie in the lack of literature that might facilitate a better SWOT analysis of POIPAT. In the future, it would be useful to perform a study to determine the cognitive value of the analysed POIPAT. Practical Implications: The paper's findings enable an insight into POIPAT's usefulness as one of the methods available for cold-case investigations. Originality/Value: This paper is one of just a few to mention the POIPAT method. It is intended for anyone interested in this subject, with police officers and criminal investigators being particularly in mind.
... These developments enable the police to incorporate lots of persons of interest around a crime scene. Sutmuller, den Hengst, Barros & van Gelder [12] showed that the incorporation of the actual perpetrator into a homicide investigation can be accelerated if categories of persons of interest are incorporated. Categories that were used: people with a relationship with the victim, people that were present in a certain geographical area, people with certain physical characteristics, people with previous convictions and people owing certain registered goods. ...
... Categories that were used: people with a relationship with the victim, people that were present in a certain geographical area, people with certain physical characteristics, people with previous convictions and people owing certain registered goods. The downside of using categories is the incorporation of a great number of persons of interest [12]. The increased number of persons of interest makes the identification of the actual perpetrator a daunting task. ...
... One possible explanation for this result is the great diversity of homicide cases. Homicide appears in many shapes and forms, ranging from criminal settlements to crime passionel, and from sexually motivated child murder to an argument gotten out of hand [12]. All these shapes and forms have different motives and perpetrators but share to some extent the same crime scene and victim characteristics. ...
Conference Paper
In this paper two Bayesian approaches and a frequency approach are compared on predicting offender output variables based on the input of crime scene and victim variables. The K2 algorithm, Naïve Bayes and frequency approach were trained to make the correct prediction using a database of 233 solved Dutch single offender/single victim homicide cases and validated using a database of 35 solved Dutch single offender/single victim homicide cases. The comparison between the approaches was made using the measures of overall prediction accuracy and confidence level analysis. Besides the comparison of the three approaches, the correct predicted nodes per output variable and the correct predicted nodes per validation case were analyzed to investigate whether the approaches could be used as a decision tool in practice to limit the incorporation of persons of interest into homicide investigations. The results of this study can be summarized as: the non-intelligent frequency approach shows similar or better results than the intelligent Bayesian approaches and the usability of the approaches as a decision tool to limit the incorporation of persons of interest into homicide investigations should be questioned.
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